Controlling oscillatory instabilities is an important aspect of a system when a device experiences the oscillatory instabilities. An oscillatory instability degrades device performance, effectively reducing lifetime of the device. Such instabilities are seen in turbulent systems such as but not limited to aero-elastic systems, hydrodynamic systems, magneto-hydrodynamic systems, aero-acoustic systems and thermoacoustic systems. As an example, in devices such as combustors that are used in gas turbines, jet engines, and industrial processing devices such as furnaces and burners, controlling and avoiding the oscillatory instability remains a challenging task as these instabilities are driven by a variety of flow and combustion processes. Further, in these devices, oscillatory instabilities may arise easily as only a small fraction of the energy available to the system is sufficient to drive such instabilities and the corresponding attenuation in the device is weak. Hence, large amplitude pressure oscillations are easily established in the devices resulting in performance loss, reduced operational range, and structural degradation due to increased heat transfer. Furthermore, detection of the onset of oscillatory instabilities remains a challenging task in flow induced vibrations due to aero-elastic instabilities and pipe tones arising due to aero acoustic instabilities. In most scenarios, these oscillations can be undesired and can deteriorate the intended functionality of the device or shut down functioning of the device. In such situations, it is required to detect and indicate the onset of oscillatory instability or an impending instability to allow a controller to take corrective measure. Thus, the corrective measure can prevent damages to the device and sustain device performance.
Conventional methods for controlling oscillatory instabilities in devices such as combustion chambers rely on measurement of pressure fluctuation in the combustion chamber to generate a delayed signal (control signal) based on the pressure fluctuation, which in turn, is used to modulate the fuel pressure inside the fuel line to actively control the instability. However, these techniques require external actuators and consume high amounts of energy for the active control. Further, the control is initiated when the instability is detected; however, occurrence of instability might have done the damage to the device.
Many existing methods provide detecting onset of the oscillatory instability, thus enabling corrective measures to prevent any oscillatory instabilities in the device. However, many of the existing methods follow a frequency domain approach, but presence of noise in the device can make it difficult to use it for practical applications as reliability of detection of the onset of oscillatory instability may be low.
Another existing method utilizes autocorrelation of the pressure signals from the combustor to characterize the damping of the system and thereby predict the stability margin. The existing method allows changes in the stability margin of each of the combustor's stable modes due to tuning, aging, or environmental changes could be monitored through an online analysis of the pressure signal. However since autocorrelation is a linear measure, there is the danger of overlooking various nonlinear dynamic characteristics prior to the instability. Further, the presence of multiple frequencies at the onset of combustion instability makes the quantification of damping unclear.
Thus, the conventional techniques for controlling the oscillatory instabilities require either incorporation of certain design features in the device or the incorporation of sensors or similar detectors that could detect the instability and further control the instability. Further, most of the processes are directed towards identifying the instability after the onset of instability.
Yet another existing method is based on anomaly detection in thermal pulse combustors using symbolic time series analysis. The existing method describes detecting thermoacoustic instability leading to blowout in pulse combustors as frictional coefficient of the tailpipe is changed. Thus, the existing method typically uses anomaly detection technique for pulse combustors.
Hence, there exists a need for a system and a method that could predetermine the onset of oscillatory instability in any turbulent system to control various parameters of the device accordingly and prevent the system from entering an operational regime where it becomes unstable, thus improving the stability margins.